DocumentCode :
183017
Title :
A novel method for diagnosing premature ventricular contraction beat based on chaos theory
Author :
Haiman Du ; Yang Bai ; Suiping Zhou ; Hongrui Wang ; Xiuling Liu
Author_Institution :
Coll. of Electron. & Inf. Eng., Hebei Univ., Baoding, China
fYear :
2014
fDate :
19-21 Aug. 2014
Firstpage :
497
Lastpage :
501
Abstract :
Premature Ventricular Contraction (PVC) is a common type of abnormal heartbeat. Without early diagnosis and proper treatment, PVC may result in more serious harms. Diagnosis of PVC is of great importance in goal-directed treatment and preoperative prognosis. In this paper, we propose a novel diagnostic method for PVC based on chaos theory, where classification of PVC from other types (normal(N), premature atrial contractions(PAC), right bundle branch block(RBBB)) of ECG beats can be done through chaotic feature extraction. To verify the effectiveness of the proposed method, a series of experiments have been conducted with data from MIT-BIH database.
Keywords :
chaos; electrocardiography; feature extraction; medical signal processing; patient diagnosis; ECG beats; MIT-BIH database; PAC; PVC; RBBB; abnormal heartbeat; chaos theory; chaotic feature extraction; diagnosing premature ventricular contraction beat; diagnostic method; goal-directed treatment; premature atrial contractions; preoperative prognosis; right bundle branch block; Chaos; Databases; Discrete wavelet transforms; Educational institutions; Electrocardiography; Feature extraction; Heart beat; Lyapunov exponents; PVC diagnosis; chaos theory; chaotic feature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2014 11th International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4799-5147-5
Type :
conf
DOI :
10.1109/FSKD.2014.6980884
Filename :
6980884
Link To Document :
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